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In the last few years, parallel manipulators are being increasingly studied and used for different applications. The performance of parallel manipulators is very sensitive to the geometric parameters, so it is essential to optimize them in order to obtain the desired function. We propose two optimization algorithms that consider the size and regularity of the workspace. The first one obtains the geometric parameters combination that results in the biggest and most regular workspace. The second method analyzes the geometric parameters combinations that result in an acceptable size of the workspace—even if it is not the biggest one—and finds out which ones result in the lowest power consumption. Even if the results vary depending on the application and trajectories studied, the proposed methodology can be followed to any type of parallel manipulator, application or trajectory. In this work we focus on the dimension optimization of the geometric parameters of the 2PRU-1PRS Multi-Axial Shaking Table (MAST) for automobile pieces testing purposes.

Optimization of the 2PRU-1PRS Parallel Manipulator Based on Workspace and Power Consumption Criteria